There is a great change about video broadcast technology in recent 20 years. For example, from analog television in the 20th century to digital television, HDTV and even 3D television we use today, the video broadcast technology is developing to improve the daily life of people. People is no longer satisfied with visual perception brought by traditional 2D video, and 3D video become a heating topic in multimedia information industry due to a sense of immediacy and interactivity. A compressed encoding method of 3D video formatted data containing more texture and depth based on HEVC (HEVC High-Efficiency Video Coding) has been developed by 3DG group of MPEG now. In July 2012, VCEG and MPEG research groups founded JCT-3V group and defined a standard of 3D video coding extension. They disclosed 3D encoding standard 3D-HEVC based on HEVC. The most efficient 3D video manifestation mode used by 3D-HEVC standard is more texture and depth video, which is obtained by more neighbor video cameras (usually shoot 3 texture and 3 depth) shoot from different angles for one sense which is multi-path video compilations with little difference in angle of view. More texture video added with more depth information will describe 3D sense information more specifically and entirely. It is useful for 3D video terminals to generate high-quality stimulation images of random view angles in a wider range of view angles; this high-quality stimulation image is generated by drawing technology of depth stimulation viewpoints and provides binocular display perception and motion parallax perception to provide an immersed viewing perception for users.
Since more texture and depth video has large quantities of data, efficiently compressed encoding has to be processed. Accordingly, researchers use 8×8 to 64×64 quadtree prediction unit construction, 4×4 to 32×32 transform unit size, 36 kinds of an intra-frame prediction mode in multi-angle, adaptive loop filter and more new technology in encoding standard disclosed by 3D-HEVC. At the same time, as for more texture and depth video encoding construction of 3D-HEVC, researchers use more reference frames between viewpoints. The conception of intra-prediction mode is extended as motion prediction encoding mode in the time direction, and disparity prediction mode in the direction of neighboring viewpoint, and the calculation difficulty is improved.
For example, more texture and depth video with 3 texture and 3 depth, as illustrated in FIG. 1, horizontal line represents time direction, vertical lines represents viewpoints direction. Hierarchical frame B to delete redundancy in the time direction is used, and I-P-P structure to delete redundancy information between viewpoints is used in viewpoint direction. The base viewpoint can only use a coding frame inner itself as a reference frame; a dependent viewpoint can use base viewpoint coding frame as reference frame except for using finished coding frame inner itself. For each viewpoint, there is a corresponding depth map characterized by 8 bit. In 3D-HEVC, first, encoding texture map of a base viewpoint, then encoding depth map of base viewpoint, and then encoding texture map and a depth map of dependent viewpoint. Since the depth map needs texture map information to encode, texture map must be coded before the depth map, which is called texture map encoding priority encoding order, as illustrated in FIG. 2.
Disparity vector obtaining is an important technology in more texture and depth 3D-HEVC video coding, and widely used in motion compensation prediction and residual prediction between viewpoints. Disparity vector represents the difference between different video frame at a same time, with current 3D-HEVC standard, disparity vector in a base viewpoint can give prediction unit of dependent viewpoint a motion compensation. In texture map encoding priority encoding order, when encoding prediction unit of dependent viewpoint, the disparity vector used cannot be calculated from corresponding texture map because the corresponding depth map is not input in the coding unit.
The traditional method is provided as follow. Through block estimation and block matching to obtain disparity vector, the method needs related information to decode in the decoding end. If this information is transported in the code stream, extra transportation bit is generated. To avoid this situation, 3D-HEVC introduces a way that estimates depth map from texture map information which is finished the encoding process. To get the depth map, disparity information between the base viewpoint and dependent viewpoint is transformed into depth information. The calculated depth information can be transformed into depth map information of base viewpoint and another dependent viewpoint. During this process, the estimated max depth value in depth map will be transformed into disparity vector; the process is called disparity vector transformation based on the depth map.
There is a large amount of calculation during the process of disparity vector transformation based on the depth map. To decrease calculation complexity, 3D-HEVC introduces simplified obtaining method of disparity vector, which is called disparity vector obtaining method based on neighboring block. Disparity vector obtaining method based on neighboring block using a pre-installed order to search for candidate space and time coding block location, judging if there have a disparity vector information to obtain disparity vector of a current block, coding block in space and time the location is shown in FIG. 3 and FIG. 4. If the searched prediction unit uses disparity compensation prediction or disparity motion compensation prediction technology, there is disparity information in prediction unit, and the first searched disparity vector is used in the process of motion compensation prediction and residual prediction between viewpoints. Searching order is: first searching CRT and BR in a time reference frame, then searching A1, B1, B0, A0 and B2 in space reference frame, and searching motion vector compensation situation of these space reference frames. Disparity vector obtaining method based on neighboring blocks can save at least 8% time compared with disparity vector transformation based on the depth map.
After the disparity vector obtaining method based on neighboring block appeared, 3D-HEVC uses disparity vector obtaining method based on a depth map of neighboring block to improve obtained neighboring disparity vector. The disparity vector obtaining method based on a depth map of the neighboring block takes depth map of base viewpoint to amend disparity vector obtained initially. After obtaining origin disparity vector of neighboring block, a max depth value of base viewpoint depth map is used to amend and get the final disparity vector.
To reduce the process of obtaining disparity vector through transform bit acceleration, some research groups study a fast algorithm for obtaining disparity vector based on neighboring block. For example, Hisilicon disclosed a searching method that skip overlap location in prediction unit, Qualcomm disclosed a method that takes coding unit as minimum algorithm taking the unit, and Samsung disclosed a method that deletes searching location in time and space reference frame (shown as FIG. 5, FIG. 6). Moreover, some research groups disclosed using of variable coding tools to change the coding order of 3D-HEVC.
In conclusion, current amend methods for disparity vector obtaining based on the neighboring block are all aimed at deleting searching location and decreasing searching times. The main problem is: first obtained disparity vector is considered as final disparity vector, searching is stopped, and there may have disparity vector which can be used and maybe better than searched one is not searched and stopped by the whole obtaining process. Accordingly, the present disclosure based on 3D-HEVC disclosed a method changes the rule of first obtained disparity vector as the final disparity vector. Through deleting the location which is minimum searched in neighboring candidate space and time coding unit location, at the same time, grouped neighboring candidate space and time coding unit location, the approach takes the searched disparity vector which is combined according to the proportion of adoption rate as final disparity vector, improving coding quality and at the same time maintaining origin fast algorithm efficiency.